Advanced biomedical imaging for accurate discrimination and prognostication of mediastinal masses
© 2023 The Authors. European Journal of Clinical Investigation published by John Wiley & Sons Ltd on behalf of Stichting European Society for Clinical Investigation Journal Foundation..
BACKGROUND: To investigate the potential of radiomic features and dual-source dual-energy CT (DECT) parameters in differentiating between benign and malignant mediastinal masses and predicting patient outcomes.
METHODS: In this retrospective study, we analysed data from 90 patients (38 females, mean age 51 ± 25 years) with confirmed mediastinal masses who underwent contrast-enhanced DECT. Attenuation, radiomic features and DECT-derived imaging parameters were evaluated by two experienced readers. We performed analysis of variance (ANOVA) and Chi-square statistic tests for data comparison. Receiver operating characteristic curve analysis and Cox regression tests were used to differentiate between mediastinal masses.
RESULTS: Of the 90 mediastinal masses, 49 (54%) were benign, including cases of thymic hyperplasia/thymic rebound (n = 10), mediastinitis (n = 16) and thymoma (n = 23). The remaining 41 (46%) lesions were classified as malignant, consisting of lymphoma (n = 28), mediastinal tumour (n = 4) and thymic carcinoma (n = 9). Significant differences were observed between benign and malignant mediastinal masses in all DECT-derived parameters (p ≤ .001) and 38 radiomic features (p ≤ .044) obtained from contrast-enhanced DECT. The combination of these methods achieved an area under the curve of .98 (95% CI, .893-1.000; p < .001) to differentiate between benign and malignant masses, with 100% sensitivity and 91% specificity. Throughout a follow-up of 1800 days, a multiparametric model incorporating radiomic features, DECT parameters and gender showed promising prognostic power in predicting all-cause mortality (c-index = .8 [95% CI, .702-.890], p < .001).
CONCLUSIONS: A multiparametric approach combining radiomic features and DECT-derived imaging biomarkers allows for accurate and noninvasive differentiation between benign and malignant masses in the anterior mediastinum.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:53 |
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| Enthalten in: |
European journal of clinical investigation - 53(2023), 12 vom: 12. Dez., Seite e14075 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Mahmoudi, Scherwin [VerfasserIn] |
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| Links: |
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| Themen: |
Artificial intelligence |
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| Anmerkungen: |
Date Completed 22.11.2023 Date Revised 22.11.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1111/eci.14075 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM360714803 |
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| 100 | 1 | |a Mahmoudi, Scherwin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Advanced biomedical imaging for accurate discrimination and prognostication of mediastinal masses |
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| 500 | |a Date Revised 22.11.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2023 The Authors. European Journal of Clinical Investigation published by John Wiley & Sons Ltd on behalf of Stichting European Society for Clinical Investigation Journal Foundation. | ||
| 520 | |a BACKGROUND: To investigate the potential of radiomic features and dual-source dual-energy CT (DECT) parameters in differentiating between benign and malignant mediastinal masses and predicting patient outcomes | ||
| 520 | |a METHODS: In this retrospective study, we analysed data from 90 patients (38 females, mean age 51 ± 25 years) with confirmed mediastinal masses who underwent contrast-enhanced DECT. Attenuation, radiomic features and DECT-derived imaging parameters were evaluated by two experienced readers. We performed analysis of variance (ANOVA) and Chi-square statistic tests for data comparison. Receiver operating characteristic curve analysis and Cox regression tests were used to differentiate between mediastinal masses | ||
| 520 | |a RESULTS: Of the 90 mediastinal masses, 49 (54%) were benign, including cases of thymic hyperplasia/thymic rebound (n = 10), mediastinitis (n = 16) and thymoma (n = 23). The remaining 41 (46%) lesions were classified as malignant, consisting of lymphoma (n = 28), mediastinal tumour (n = 4) and thymic carcinoma (n = 9). Significant differences were observed between benign and malignant mediastinal masses in all DECT-derived parameters (p ≤ .001) and 38 radiomic features (p ≤ .044) obtained from contrast-enhanced DECT. The combination of these methods achieved an area under the curve of .98 (95% CI, .893-1.000; p < .001) to differentiate between benign and malignant masses, with 100% sensitivity and 91% specificity. Throughout a follow-up of 1800 days, a multiparametric model incorporating radiomic features, DECT parameters and gender showed promising prognostic power in predicting all-cause mortality (c-index = .8 [95% CI, .702-.890], p < .001) | ||
| 520 | |a CONCLUSIONS: A multiparametric approach combining radiomic features and DECT-derived imaging biomarkers allows for accurate and noninvasive differentiation between benign and malignant masses in the anterior mediastinum | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a artificial intelligence | |
| 650 | 4 | |a iodine | |
| 650 | 4 | |a mediastinal neoplasm | |
| 650 | 4 | |a mediastinum | |
| 650 | 4 | |a multidetector computed tomography | |
| 650 | 4 | |a thymoma | |
| 700 | 1 | |a Gruenewald, Leon D |e verfasserin |4 aut | |
| 700 | 1 | |a Eichler, Katrin |e verfasserin |4 aut | |
| 700 | 1 | |a Martin, Simon S |e verfasserin |4 aut | |
| 700 | 1 | |a Booz, Christian |e verfasserin |4 aut | |
| 700 | 1 | |a Bernatz, Simon |e verfasserin |4 aut | |
| 700 | 1 | |a Lahrsow, Maximilian |e verfasserin |4 aut | |
| 700 | 1 | |a Yel, Ibrahim |e verfasserin |4 aut | |
| 700 | 1 | |a Gotta, Jennifer |e verfasserin |4 aut | |
| 700 | 1 | |a Biciusca, Teodora |e verfasserin |4 aut | |
| 700 | 1 | |a Mohammed, Hanin |e verfasserin |4 aut | |
| 700 | 1 | |a Ziegengeist, Nicole Suarez |e verfasserin |4 aut | |
| 700 | 1 | |a Torgashov, Katerina |e verfasserin |4 aut | |
| 700 | 1 | |a Hammerstingl, Renate M |e verfasserin |4 aut | |
| 700 | 1 | |a Sommer, Christof M |e verfasserin |4 aut | |
| 700 | 1 | |a Weber, Christophe |e verfasserin |4 aut | |
| 700 | 1 | |a Almansour, Haidara |e verfasserin |4 aut | |
| 700 | 1 | |a Bucolo, Giuseppe |e verfasserin |4 aut | |
| 700 | 1 | |a D'Angelo, Tommaso |e verfasserin |4 aut | |
| 700 | 1 | |a Scholtz, Jan-Erik |e verfasserin |4 aut | |
| 700 | 1 | |a Gruber-Rouh, Tatjana |e verfasserin |4 aut | |
| 700 | 1 | |a Vogl, Thomas J |e verfasserin |4 aut | |
| 700 | 1 | |a Koch, Vitali |e verfasserin |4 aut | |
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